About

Todd Dawson is a Distinguished Professor whose research focuses on the interface between plants and their natural and human-impacted environments. His work employs tools such as physiological plant ecology, stable isotope biogeochemistry, ecohydrology, and remote sensing to study and interpret these interfaces. His investigations draw upon a wide range of physiological methods, observations, experiments, modeling, and the use of stable isotopes to enhance understanding of how the ecophysiological characteristics of plants are shaped by and respond to their environments. Dawson's projects pay special attention to how plant form and function enable adaptation to environmental variation, whether natural or anthropogenic, and how these traits influence community and ecosystem structure and function, with a particular emphasis on woody plants and forest systems.

Research topics

• Environmental science
• Biology
• Ecology
• Botany
• Agronomy

Selected publications

• Will epiphyte loss exacerbate climate change effects in tropical montane cloud forests?

  Agricultural and Forest Meteorology · 2026-01-04

  article
  PublisherDOI

• Dataset: Will epiphyte loss exacerbate climate change effects in tropical montane cloud forests?

  Figshare · 2026-01-01

  datasetOpen access

  Note: This is copied and pasted from the attached Word doc ("Figshare metadata"). It might be easier to read it there.<b>R scripts</b>· 1_Functions_RxMC: Functions used in the data processing and analysis scripts· 2_Data_processing_RxMC: Script used to process intermediate data that is used for analysis· 3_Analysis_RxMC: Run analyses, generate figures and output tables<br><b>Datasets</b>Note: Some additional data processing is done in the script “2_Data_processing_RxMC”, but all data needed for that script is included here.· Base_tree_data.csv: Full dataset of microclimate data from all 20 trees over the study time period· Reference_data_full.csv: Full dataset of microclimate data from all 5 reference stations over the study time period· Epi_mat_weight.csv: Data from the epiphyte mat water holding capacity part of the study.· Leaf_off_by_pair_new.csv: A dataset, at 15-min resolution, that identifies times when leaves were absent for each tree. Meant to be joined to main dataset to filter out those periods.· Tree_metadata.csv: Metadata for each tree, explained below in more detail.<br><b>Key columns appearing in multiple datasets</b>· Tree: Unique Tree or reference station identifier used in the study, of 25 total. Although reference stations are not trees, the same column header is used to facilitate binding dataframes by column name.· Station: Location of specific sensor within the tree.o S0: Denotes reference stationo S1-S3: Outer-canopy stationso S4: Inner canopy stationo S5: Above-canopy station· Timestamp: Hourly as y-m-d h:m:s or daily as ymd. Reading into R with lubridate::as_datetime() works like a charm<br><b>Microclimate variables explained</b>These variables appear in base tree data and reference data· Solar: Solar radiation (W/m²)· Temp: Temperature (°C)· RH: Relative humidity (proportion)· Atmos_pressure: Atmospheric pressure (kPa)· VPD: Vapor Pressure Deficit (kPa)· LW_minutes: Number of minutes that leaves were wet out of the previous 15 (proportion)· Wetness: Leaf wetness (g/m²)· Wind_speed: Wind speed (m/s)· Precipitation: Water input to pluviometers (mm)<br><b>Tree metadata columns</b>· Pair: Identifier for partner tree· Reference: Identifier for the closest reference station· Land: Forest or pasture· Treatment: Stripped or control· Genus<br><b>Epiphyte water holding capacity columns</b>· Saturated weight (kg): Weight after being soaked overnight in water and drip-drying for approximately 30 min.· Dried weight (kg): Weight after oven-drying for 3 days

  PublisherDOI

• Will epiphyte loss exacerbate climate change effects in tropical montane cloud forests?

  Figshare · 2026-01-01

  datasetOpen access

  Note: This is copied and pasted from the attached Word doc ("Figshare metadata"). It might be easier to read it there.<b>R scripts</b>· 1_Functions_RxMC: Functions used in the data processing and analysis scripts· 2_Data_processing_RxMC: Script used to process intermediate data that is used for analysis· 3_Analysis_RxMC: Run analyses, generate figures and output tables<br><b>Datasets</b>Note: Some additional data processing is done in the script “2_Data_processing_RxMC”, but all data needed for that script is included here.· Base_tree_data.csv: Full dataset of microclimate data from all 20 trees over the study time period· Reference_data_full.csv: Full dataset of microclimate data from all 5 reference stations over the study time period· Epi_mat_weight.csv: Data from the epiphyte mat water holding capacity part of the study.· Leaf_off_by_pair_new.csv: A dataset, at 15-min resolution, that identifies times when leaves were absent for each tree. Meant to be joined to main dataset to filter out those periods.· Tree_metadata.csv: Metadata for each tree, explained below in more detail.<br><b>Key columns appearing in multiple datasets</b>· Tree: Unique Tree or reference station identifier used in the study, of 25 total. Although reference stations are not trees, the same column header is used to facilitate binding dataframes by column name.· Station: Location of specific sensor within the tree.o S0: Denotes reference stationo S1-S3: Outer-canopy stationso S4: Inner canopy stationo S5: Above-canopy station· Timestamp: Hourly as y-m-d h:m:s or daily as ymd. Reading into R with lubridate::as_datetime() works like a charm<br><b>Microclimate variables explained</b>These variables appear in base tree data and reference data· Solar: Solar radiation (W/m²)· Temp: Temperature (°C)· RH: Relative humidity (proportion)· Atmos_pressure: Atmospheric pressure (kPa)· VPD: Vapor Pressure Deficit (kPa)· LW_minutes: Number of minutes that leaves were wet out of the previous 15 (proportion)· Wetness: Leaf wetness (g/m²)· Wind_speed: Wind speed (m/s)· Precipitation: Water input to pluviometers (mm)<br><b>Tree metadata columns</b>· Pair: Identifier for partner tree· Reference: Identifier for the closest reference station· Land: Forest or pasture· Treatment: Stripped or control· Genus<br><b>Epiphyte water holding capacity columns</b>· Saturated weight (kg): Weight after being soaked overnight in water and drip-drying for approximately 30 min.· Dried weight (kg): Weight after oven-drying for 3 days

  PublisherDOI

• Trait plasticity enables trees and shrubs to live as epiphytes throughout the coast redwood canopy

  Ecosphere · 2026-04-01

  articleOpen access

  Abstract The radiation of plants into epiphytic niches has largely been studied by comparing closely related taxa that contain both epiphytic and terrestrial species. While these studies have led to important insights, they leave unanswered an important question—what traits allow for the initial colonization of the epiphytic niche? Our study addressed this knowledge gap in an old‐growth coast redwood ( Sequoia sempervirens ) forest, which has few obligate epiphytes but an abundance of accidental epiphytes. We measured structural and water relations traits in four woody species that are largely terrestrial but also commonly exist as epiphytes in the canopy of coast redwood forests: Vaccinium ovatum , V. parvifolium , Gaultheria shallon , and Tsuga heterophylla . We also measured these traits on one obligate epiphytic fern Polypodium scouleri , and one obligate terrestrial fern, Polystichum munitum . Traits were measured across a height gradient from ground level to the upper canopy (68.9–92.4 m). We found that accidental epiphytes exhibited many trait shifts as they occupied higher niches. Height above the ground explained significant variation in stomatal density, specific leaf area (SLA), leaf thickness, and stable isotope composition, which likely are responses to increases in light and decreases in water availability. Despite consistent variation of some traits with height, our study also highlights unique trait combinations for different taxa living as epiphytes. It is extremely rare to study within‐species trait shifts that enable normally terrestrial species to occur as epiphytes, and our study uniquely leveraged the lengthy ground‐to‐canopy height gradient offered by this coast redwood forest to resolve how and why some species are able to make the transition to epiphytism. We found consistent variation in the expression of SLA, stomatal density, turgor loss point, and minimum leaf conductance between terrestrial and epiphytic individuals, despite our focal taxa including a wide range of growth forms (i.e., ferns, shrubs, and trees). These results highlight the potential importance of trait variation in supporting an evolutionary niche shift towards epiphytism. In contrast, some traits we measured exhibited inconsistent variation between epiphytic and terrestrial individuals, indicating that despite some coordinated trait shifts, unique trait combinations facilitate the colonization of the epiphytic niche.

  PublisherDOI

• Dataset: Will epiphyte loss exacerbate climate change effects in tropical montane cloud forests?

  Figshare · 2026-01-01

  datasetOpen access

  Note: This is copied and pasted from the attached Word doc ("Figshare metadata"). It might be easier to read it there.<b>R scripts</b>· 1_Functions_RxMC: Functions used in the data processing and analysis scripts· 2_Data_processing_RxMC: Script used to process intermediate data that is used for analysis· 3_Analysis_RxMC: Run analyses, generate figures and output tables<br><b>Datasets</b>Note: Some additional data processing is done in the script “2_Data_processing_RxMC”, but all data needed for that script is included here.· Base_tree_data.csv: Full dataset of microclimate data from all 20 trees over the study time period· Reference_data_full.csv: Full dataset of microclimate data from all 5 reference stations over the study time period· Epi_mat_weight.csv: Data from the epiphyte mat water holding capacity part of the study.· Leaf_off_by_pair_new.csv: A dataset, at 15-min resolution, that identifies times when leaves were absent for each tree. Meant to be joined to main dataset to filter out those periods.· Tree_metadata.csv: Metadata for each tree, explained below in more detail.<br><b>Key columns appearing in multiple datasets</b>· Tree: Unique Tree or reference station identifier used in the study, of 25 total. Although reference stations are not trees, the same column header is used to facilitate binding dataframes by column name.· Station: Location of specific sensor within the tree.o S0: Denotes reference stationo S1-S3: Outer-canopy stationso S4: Inner canopy stationo S5: Above-canopy station· Timestamp: Hourly as y-m-d h:m:s or daily as ymd. Reading into R with lubridate::as_datetime() works like a charm<br><b>Microclimate variables explained</b>These variables appear in base tree data and reference data· Solar: Solar radiation (W/m²)· Temp: Temperature (°C)· RH: Relative humidity (proportion)· Atmos_pressure: Atmospheric pressure (kPa)· VPD: Vapor Pressure Deficit (kPa)· LW_minutes: Number of minutes that leaves were wet out of the previous 15 (proportion)· Wetness: Leaf wetness (g/m²)· Wind_speed: Wind speed (m/s)· Precipitation: Water input to pluviometers (mm)<br><b>Tree metadata columns</b>· Pair: Identifier for partner tree· Reference: Identifier for the closest reference station· Land: Forest or pasture· Treatment: Stripped or control· Genus<br><b>Epiphyte water holding capacity columns</b>· Saturated weight (kg): Weight after being soaked overnight in water and drip-drying for approximately 30 min.· Dried weight (kg): Weight after oven-drying for 3 days

  PublisherDOI

• Increased Groundwater Dependence of Riparian Vegetation in Response to Drought

  Ecohydrology · 2025-07-01 · 1 citations

  articleOpen access

  ABSTRACT Riparian ecosystems in drylands face increasing risks from intensifying droughts, which lower water tables, reduce soil moisture and suppress streamflow—threatening vegetation and risking ecosystem collapse. Although riparian vegetation relies on subsurface water, the relative importance of groundwater versus rainfall‐infiltrated soil moisture during drought remains unclear. As climate change prolongs drought severity, understanding how plants shift between water sources is key to predicting ecosystem resilience and guiding sustainable groundwater management. We conducted a stable isotope study along the Santa Clara River in southern California (2018–2020) during recovery from a severe (2012–2019) drought. We sampled δ 18 O p in plant xylem water from four native riparian woody species ( Salix exigua , S. laevigata , Populus trichocarpa , P. fremontii ) and the non‐native grass Arundo donax . Shallow soil moisture and groundwater were sampled to characterize endmember δ 18 O signatures. Isotope mixing models were developed to track shifts in water source contributions for each species over three growing seasons. Riparian plants showed opportunistic water use, relying on shallow soil moisture during wet periods and shifting to groundwater during droughts. Native taxa including Populus and Salix species increased groundwater use by up to 60% during drought, reflecting hydraulic flexibility and drought tolerance. In contrast, the invasive A. donax depended on shallow soil moisture for 64–86% of its water under all conditions. These findings underscore the importance of quantifying species‐ and site‐specific groundwater use. Incorporating such ecological insights into groundwater sustainability planning will be critical for protecting riparian vegetation and maintaining ecosystem function in a changing climate.

  PublisherOA PDFDOI

• Drought limits foliar water uptake in C3 perennial grasses

  2025-04-06

  preprintOpen access

  Rain, fog, and dew can all provide the conditions necessary to induce direct uptake of water into the foliage of plants. Although grasslands are known to have frequent leaf-wetting events, the capacity of grasses to conduct foliar water uptake has never been explicitly quantified. Here, we show the results of greenhouse experiments used to quantify foliar water uptake during leaf wetting and characterize the importance of foliar water uptake during drought. Across the species tested, we found an average foliar water uptake of 3.34 ± 0.32 [mg H2O cm-2] which represented a leaf water content increase of 8.82 ± 0.95 % over a three-hour leaf wetting treatment. We show that leaves with higher wettability exhibit lower resistance to foliar water uptake, consistent with previous theory. Our results indicate that foliar water uptake occurs in C3 perennial grasses and can provide relief during drought. However, we found that the benefits resulting from foliar water uptake decrease as drought becomes severe and plants close their stomata to conserve water.

  PublisherOA PDFDOI

• A novel model quantifies epiphyte-mediated temperature and water dynamics in a tropical montane cloud forest

  Agricultural and Forest Meteorology · 2025-08-23 · 2 citations

  articleOpen access

  Tropical montane cloud forests (TMCFs) are ecosystems with high biodiversity that are threatened by deforestation, land use changes, and climate change. One of the unique aspects of TMCFs is the high biomass and diversity of epiphytes. Epiphytes are vascular and non-vascular plants that live in tree canopies, creating arboreal micro-ecosystems. They provide ecological services by capturing and retaining allochthonous nutrients from rain and fog, and by supporting the presence of canopy pollinators and other fauna. Predicted changes in cloudiness and land conversion threaten the abundance of epiphytes, and thus their capacity to contribute to ecosystem functions. However, how losses in epiphyte abundance will affect microclimate and host tree water status is still unclear and requires the ability to simulate the role of epiphytes in canopy water storage dynamics. We developed a water balance model for epiphytes in TMCFs. We consider epiphytes in the host tree as a water store inside the canopy that is filled via precipitation from both rain and fog, and depleted via evapotranspiration and host tree water uptake. The model was used to simulate water and energy fluxes between the epiphytes and their surroundings under idealized and real dry season conditions for TMCFs near Monteverde, Costa Rica. Results from the idealized and real simulations capture how epiphytes retain water under dry-down conditions, leading to small diurnal variability in temperature, low evapotranspiration rates, and enhanced dew deposition at night. We find that dew deposition recharges up to 34 % of epiphyte water storage lost due to evapotranspiration over a 3-day dry-down event. Our results provide the first quantitative demonstration of the importance of epiphyte water storage on temperature and dew formation in TMCFs. This work sets the foundation for developing a process-based understanding of the effects of epiphyte loss on TMCF ecohydrology. • A mechanistic model for water and energy fluxes in epiphyte mats was developed. • Simulated epiphyte mat temperatures were within 1 °C of observations. • Nighttime epiphyte mat temperatures consistently fall to air dew point temperatures. • Nighttime dew deposition refilled up to 34% of water lost through evapotranspiration. • Depletion of epiphytic water stores leads to increases in evapotranspiration.

  PublisherDOI

• Groundwater and Remotely Sensed Phenology Reveal Vulnerability of Riparian Trees to Drought

  Global Change Biology · 2025-10-01

  articleOpen access

  The increasing frequency and magnitude of climatic extremes are altering water availability in dryland ecosystems globally. However, riparian vulnerability to hydroclimate whiplash remains poorly understood. Here, we examined how riparian willow, cottonwood, and valley oak trees respond to groundwater fluctuations and drought through their water use patterns and phenology. To this end, we combined time-series analysis of in situ, high-frequency groundwater monitoring with high-resolution PlanetScope satellite imagery of a drought-prone and relatively pristine watershed in California (Chalone Creek, Pinnacles National Park). We found that flow regime dictates the potential for trees to access groundwater, while the identity of tree species determines the timing and magnitude of their use. Machine-learning models revealed that at intermittent sites groundwater depth predominantly controlled vegetation greenness, represented by the Normalized Difference Vegetation Index (NDVI). In contrast, variation in photoperiod length dominated at the perennial site where water was more reliably available. During the severe 2020-2022 drought, all species experienced reduced greenness, but phenological responses differed by flow regime. While the start of the season was delayed across all sites, trees at intermittent reaches exhibited a substantially earlier end of season during drought, resulting in growing seasons shortened by as much as 37 days. These phenological shifts vastly exceed those documented across aridity classifications in global datasets from satellite observations, ground-based monitoring networks, and experimental precipitation manipulations. Although riparian trees in drylands have been shaped by exposure to drought over evolutionary timescales, our findings show that trees in these intermittent systems may be operating close to critical groundwater thresholds, rendering them particularly vulnerable to increasingly long and severe droughts.

  PublisherOA PDFDOI

• Groundwater and phenology data reveal vulnerability of riparian trees to drought

  bioRxiv (Cold Spring Harbor Laboratory) · 2025-05-28

  preprintOpen access

  Abstract The increasing frequency and magnitude of climatic extremes are altering water availability in dryland ecosystems globally. However, riparian vulnerability to hydroclimate whiplash remains poorly understood. Here, we examined how riparian trees respond to groundwater fluctuations and drought through their water use patterns and phenology. To this end, we combined time-series analysis of long-term, high-frequency groundwater monitoring and satellite imagery from a drought-prone and relatively pristine watershed in California (Chalone Creek, Pinnacles National Park). We found that trees by intermittent river reaches displayed consistent but depth-limited groundwater reliance, while those at perennial reaches primarily relied on groundwater during the dry season. Machine-learning models revealed that at intermittent sites groundwater depth predominantly controlled vegetation greenness, represented by Normalized Difference Vegetation Index (NDVI). In contrast, variation in photoperiod length dominated at perennial sites where water was more reliably available. During the severe 2020-2022 drought, all species experienced reduced greenness, but phenological responses differed by flow regime. While the start of season was delayed across all sites, trees at intermittent reaches exhibited substantially earlier end of season during drought, resulting in growing seasons shortened by as much as 28 days. These phenological shifts vastly exceed those documented across aridity classifications in global datasets from satellite observations, ground-based monitoring networks, and experimental precipitation manipulations. Although riparian trees in drylands have been shaped by exposure to drought over evolutionary timescales, our findings challenge the prevailing assumption that ecosystems regularly exposed to hydrological are more resilient to drought. Instead, we show that trees in intermittent systems may be operating close to critical groundwater thresholds, rendering them particularly vulnerable to increasingly long and severe droughts.

  PublisherOA PDFDOI

Recent grants

• RAPID: The Endless Summer: Implications of a 100-year drought for the functional biology of native Californian plants and ecosystems

  NSF · $180k · 2014–2016

• RCN: Biogeosphere-Atmosphere Stable Isotopes Network (BASIN)

  NSF · $682k · 2006–2012

• A Synergistic Approach of Using Fluxes, Isotopes and Models to Partition Plant and Soil Contributions to Ecosystem Exchange of CO2 and H2O

  NSF · $550k · 2003–2008

• Collaborative Research: Late Holocene Climate Variability From Stable Isotope Ratio Analysis of Coast Redwood Tree Ring Cellulose

  NSF · $331k · 2010–2015

Frequent coauthors

• John S. Roden

  Ashland (United States)

  43 shared

• J. B. Gaudinski

  University of California, Berkeley

  34 shared

• W. E. Dietrich

  Planetary Science Institute

  30 shared

• Darren R. Sandquist

  California State University, Fullerton

  27 shared

• Susan Trumbore

  27 shared

• Inez Fung

  26 shared

• David D. Ackerly

  University of California, Berkeley

  26 shared

• Edward A. G. Schuur

  Northern Arizona University

  26 shared

Education

• PhD, Botany

  University of Washington

• BA Biology

  University of California Santa Cruz

  1980